Do Alternative Real Estate Investment Vehicles Add Value to REITs? Evidence from German Open-ended Property Funds

Besides the more commonly used REITs, German investors can also invest in a lesser-known real estate vehicle, Open-ended Property Funds. OPFs are considered a compromise between listed and direct real estate investments. OPF fund managers generally provide daily (perfect) liquidity. However, if liquidity falls below 5%, share redemptions in these funds can be temporarily suspended for a period of up to two years. During this time, investors will only be able to sell shares on the secondary market (exchange), and are thus subject to significant liquidity risk. The objective of this paper is to analyze whether OPFs add value to investor portfolios above that provided by REITs. We show that OPFs have a diversification advantage over REITs in low-risk portfolios, despite their larger potential liquidity risk. REIT liquidity is comparable to that of ordinary common stock, but OPFs exhibit an average initial discount to funds’ NAV of about 6% when share redemptions are temporarily suspended. However, in the long-run, this potential redemption suspension does not negatively influence OPF performance (in case OPFs reopen again). This makes OPFs an attractive investment alternative to REITs for investors who have a high level of risk aversion and a long-term investment horizon, such as endowments, insurance companies, and pension funds.     

Multilevel dual approach for pricing American style derivatives

In this article we propose a novel approach to reduce the computational complexity of the dual method for pricing American options. We consider a sequence of martingales that converges to a given target martingale and decompose the original dual representation into a sum of representations that correspond to different levels of approximation to the target martingale. By next replacing in each representation true conditional expectations with their Monte Carlo estimates, we arrive at what one may call a multilevel dual Monte Carlo algorithm. The analysis of this algorithm reveals that the computational complexity of getting the corresponding target upper bound, due to the target martingale, can be significantly reduced. In particular, it turns out that using our new approach, we may construct a multilevel version of the well-known nested Monte Carlo algorithm of Andersen and Broadie (Manag. Sci. 50:1222–1234, 2004) that is, regarding complexity, virtually equivalent to a non-nested algorithm. The performance of this multilevel algorithm is illustrated by a numerical example.     

Consumption smoothing in Russia1

Using a panel from the Russian Longitudinal Monitoring Survey (1994–2004), this paper investigates to what extent Russian households have been able to maintain their living standards while suffering income shocks. Consumption smoothing is modelled by means of an equilibrium correction mechanism, which disentangles short‐run dynamics and long‐run equilibrium adjustments. GMM estimation is used to control for individual household effects in the presence of dynamics. Additionally, we differentiate between food and non‐food consumption, positive and negative shocks, rural and urban areas, and several levels of poverty risk. We find that dynamics are important in the consumption equation, and that estimates are sensitive to imputation errors in home food production. No strong claims can be made regarding heterogeneity in smoothing behaviour.     

Agricultural disaster payments in the southeastern US: do weather and climate variability matter?

Governments around the world are forced to react to disasters caused by weather. The agricultural sector is particularly susceptible to weather extremes and adverse climate conditions. In the US, agricultural disaster payments account for a significant part of total agricultural subsidies. The payments, and their distribution, are more important in the areas most affected by disastrous weather events, usually coinciding with areas of pronounced impact of the El Nino Southern Oscillation (ENSO). In this article, the impact of weather and climate, as well as some economic variables, on disaster payments is analysed using county level data from four states in the southeastern United States. The results suggest that weather and climate variables explain most of the crop disaster payments at the county level while socioeconomic variables do not, suggesting that advancements in weather and climate forecasts could be helpful in planning for disaster compensation.     

The Economic Relevance of Environmental Disclosure and its Impact on Corporate Legitimacy: An Empirical Investigation

In determining its environmental disclosure strategy, a firm's management faces a tension between responding to the information needs of financial markets and maintaining its legitimacy within the community. In this paper, relying on information economics and legitimacy theory, we explore how firms resolve this tension. Results show that a firm's environmental disclosure enhances the quality of analysts' information context, which ultimately allows them to make better forecasts. Moreover, financial analysts seem to be able to decipher environmental information, discounting discourses that are inconsistent with a firm's underlying environmental performance. We find also that a firm's environmental disclosure serves another purpose, as it influences how its other stakeholders (beyond financial ones) perceive its legitimacy. Such enhanced legitimacy reduces the information uncertainty faced by financial analysts. Our results suggest also that both economic‐based environmental disclosure and sustainable development and environmental disclosure are useful to analysts in making their forecasts and enhance a firm's legitimacy. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment.     

Organizational harm,legal condemnation and stakeholder retaliation: A typology,research agenda and application

The essence of the ethical issues pertinent to business activities is the harm or benefit that occurs as part of a company's resource transformation process. A typology is developed that sorts ethical issues according to three variables: (1) the nature of the harm, (2) the nature of those harmed and (3) the transformation stage where the harm occurs. Propositions are formulated that would enable analysts and practitioners to predict the degree of legal condemnation of, and stakeholder retaliation to, harms generated by questionable moral reasoning. An organizational harm analysis is then constructed as a decision making tool that could supplement cost/benefit analysis.Denis Collins is a Doctoral Candidate at the Katz Graduate School of Business of the University of Pittsburgh and a Research Associate with the BG Productivity and Gainsharing Institute. He has published several articles in the areas of business ethics, social philosophy and participatory management.     

Quantiles of the Euler Scheme for Diffusion Processes and Financial Applications

In this paper we briefly present the results obtained in our paper ( Talay and Zheng 2002a ) on the convergence rate of the approximation of quantiles of the law of one component of  ( X_t )  , where  ( X_t )  is a diffusion process, when one uses a Monte Carlo method combined with the Euler discretization scheme. We consider the case where  ( X_t )  is uniformly hypoelliptic (in the sense of Condition (UH) below), or the inverse of the Malliavin covariance of the component under consideration satisfies the condition (M) below. We then show that Condition (M) seems widely satisfied in applied contexts. We particularly study financial applications: the computation of quantiles of models with stochastic volatility, the computation of the VaR of a portfolio, and the computation of a model risk measurement for the profit and loss of a misspecified hedging strategy.